Course coordinator
Associate Professor Mehmet Kizil
Tue 11:00 - 12:00 or email for an appointment.
Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mech & Mine Engineering School
This course presents a systems approach to the principles, design and application of the major surface and underground mining methods together with the associated equipment, services and infrastructure. Furthermore, the course provides an introductory overview of automation and its diverse applications in both surface and underground mining contexts.
This course provides an in-depth exploration of major mining methods, the associated equipment, and essential support infrastructure. Students will gain the skills and knowledge to:
- Identify, assess, and select mining systems appropriate for various types of deposits, ensuring optimal extraction methods.
- Design and evaluate materials handling and transport options, enhancing the efficiency and safety of mining operations.
- Appraise mining systems from multiple perspectives, focusing on safety, efficiency, economics, and environmental and social responsibility.
- Identify and evaluate core risks within each mining system, developing strategies to mitigate potential hazards.
- Demonstrate awareness of major technological trends, including the impact of automation on modern mining practices.
By the end of the course, students will be equipped with a comprehensive understanding of mining systems, enabling them to make informed decisions that promote sustainable and responsible mining operations.
Course requirements
Assumed background
This course assumes that students have a good understanding of mining terms and descriptions, have been exposed to surface and underground mining methods and are familiar with mining development, operations and production.
Incompatible
You can't enrol in this course if you've already completed the following:
MINE3122
Course contact
Course staff
Lecturer
Adjunct Professor Warren Seib
Teaching staff
Mr Henry Hall
Fiona McGann
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The aim of this course is to provide students with the capability to select the appropriate mining method, together with its associated equipment, services and infrastructure, for a given deposit as well as comprehend the technological developments in mineﾠautomation.ﾠ
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Select the mining method most appropriate for a deposit in the presence of a limited set of constraints.
LO2.
Appraise mining methods with respect to metrics such as productivity, safety, sustainability and risk
LO3.
Describe and illustrate major mining methods using geotechnical and mechanical components of a range of common mining methods, along with their supporting infrastructure.
LO4.
Identify the key performance drivers and constraints of a range of common mining methods.
LO5.
Apply the systems approach to mining by Identifying the aspects of mining methods and equipment that best represent inputs, outputs, key drivers and constraints.
LO6.
Recognise major technological trends in mining such as data science and automation in mining projects.
LO7.
Enhance collaborative competencies and master advanced oral and written communication techniques to effectively contribute to team-based projects.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Paper/ Report/ Annotation, Project |
Group Assignment - Surface Mining
|
35% |
5/09/2025 1:00 pm |
| Paper/ Report/ Annotation, Project |
Group Assignment - Underground Mining
|
35% |
17/10/2025 1:00 pm |
| Paper/ Report/ Annotation, Project |
Individual Assignment with pass/fail presentation (oral examination) - Mining Technology
|
30% |
31/10/2025 1:00 pm |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Group Assignment - Surface Mining
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Project
- Weight
- 35%
- Due date
5/09/2025 1:00 pm
- Other conditions
- Peer assessed.
- Learning outcomes
- L01, L02, L03, L04, L05, L07
Task description
This project assignment is about a selection, design and productivity estimate of a surface mining system across different commodities. Students are required to work in groups, share the project workload, have weekly meetings and discussions and share the outcome of their project in a formal group report.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
Marking criteria will be provided on Blackboard.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Each team should submit one copy electronically through Turnitin on Blackboard. A peer review is also required to determine each student's contribution to the project.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Extensions impact other members of the team. Feedback is provided to students following 14 days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Group Assignment - Underground Mining
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Project
- Weight
- 35%
- Due date
17/10/2025 1:00 pm
- Other conditions
- Peer assessed.
- Learning outcomes
- L01, L02, L03, L04, L05, L07
Task description
This project assignment is about a selection, design and productivity estimate of an underground mining system across different commodities. Students are required to work in groups, share the project workload, have weekly meetings and discussions and share the outcome of their project in a formal group report.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
Marking criteria will be provided on Blackboard.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Each team should submit one copy electronically through Turnitin on Blackboard. A peer review is also required to determine each student's contribution to the project.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Extensions impact other members of the team. Feedback is provided to students following 14 days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Individual Assignment with pass/fail presentation (oral examination) - Mining Technology
- Hurdle
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Project
- Weight
- 30%
- Due date
31/10/2025 1:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05, L06
Task description
This assignment is about mining technology and automation across different commodities. This is an individual assignment and students are required to share the outcome of their project in a formal report and through a pass/fail oral examination to defend their project.
Marking criteria will be provided on Blackboard.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
Students must pass the oral examination component of the assessment to receive a passing grade for the course.Submission guidelines
Submit your report via Turnitin.
The oral examination will be scheduled at a mutually agreeable time in Week 13.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
If you are applying for an extension to the oral examination please ensure you have your correct date and time in your request. You must provide evidence in your request that demonstrates your inability to attend the oral examination at your scheduled date and time. As the oral examination is timed assessment, discretionary extensions and extensions based on Student Access Plans (SAPs) will not be accepted for the laboratory session.
Feedback is provided to students following 14 calendar days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Failure to conduct the oral examination at the scheduled date and time, without an approved extension will result in a 100% penalty.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0.00 - 29.99 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30.00 - 44.99 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45.00 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Falls short of satisfying basic requirements for a Pass. Overall grade: 45.00-49.99% or a fail grade in the IVA requirement explained below. |
| 4 (Pass) | 50.00 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Satisfies all of the basic learning requirements for the course, such as knowledge of fundamental concepts and performance of basic skills; demonstrates sufficient quality of performance to be considered satisfactory or adequate or competent or capable in the course. Overall grade 50.00-64.99% and a pass in the IVA requirement explained below. |
| 5 (Credit) | 65.00 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Demonstrates ability to use and apply fundamental concepts and skills of the course, going beyond mere replication of content knowledge or skill to show understanding of key ideas, awareness of their relevance, some use of analytical skills, and some originality or insight. Overall grade 65.00-74.99 and a pass in the IVA requirement explained below. |
| 6 (Distinction) | 75.00 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Demonstrates awareness and understanding of deeper and subtler aspects of the course, such as ability to identify and debate critical issues or problems, ability to solve non-routine problems, ability to adapt and apply ideas to new situations, and ability to invent and evaluate new ideas. Overall grade 75.00-84.99% and a pass in the IVA requirement explained below. |
| 7 (High Distinction) | 85.00 - 100.00 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Demonstrates imagination, originality or flair, based on proficiency in all the learning objectives for the course; work is interesting or surprising or exciting or challenging or erudite. Overall grade 85.00-100% and a pass in the IVA requirement explained below. |
Additional course grading information
Grading Criteria
Specific grading criteria will be provided for each assessment item. These are available on Blackboard in the assessment folder.
Identity verified assessment.
Students must pass the oral examination component of the Individual Assignment - Mining Technology to receive a passing grade for the course.
Students who do not pass the oral examination component of the Individual Assignment - Mining Technology but otherwise receive more than 50% overall, will receive a grade of 3.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Assessment items submitted using the Turnitin link on the course Blackboard site, will check your work for evidence of plagiarism, collusion, and other forms of academic misconduct.
A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Peer Assessment:
Group performance is a key component of the assessment for this course. The sole measure of performance of teamwork is by peer review. Teams which are having problems with unproductive or non-cooperative members are encouraged to seek the intervention of the course coordinator as early as possible. Do not leave these problems to the last minute. The PEER REVIEW is required for all group assessments. An online tool will be used to collect Self and Peer Assessment data. These data will be used to provide feedback to, and receive feedback from, your group members regarding contributions to the project.
Based on a series of answers from each group member the Peer Assessment Tool automatically produces two weighting factors. The SPA or Self and Peer Assessment factor is a measure of how the group overall viewed the contribution of each member of the group. This factor will be used to adjust the group mark for the project into an individual mark.
Individual mark = Group mark x Individual’s SPA
For example; a student who receives an SPA factor of 0.9 for their project contributions, reflecting a lower than average team contribution as perceived by a combination of themselves and their peers, would receive an individual mark of 72% if their group project mark was 80%.
The second factor calculated is the SAPA factor. This is the ratio of a student’s own self assessment rating compared to the average rating of their contribution by their peers. It provides students with feedback about how the rest of the group perceives their contribution. For example, a SAPA factor greater than 1 means that a student has rated their own performance higher than they were rated by their peers. Conversely, a SAPA factor less than 1 means that a student has rated their own performance lower than they were rated by their peers.
Both factors for each student will be released to all group members.
The idea of using an online peer assessment tool is not only to make group work fairer and provide feedback on your performance but to encourage the development of your professional skills. These skills include giving and receiving both positive and negative feedback, conflict resolution, collaboration, the ability to assess both your work and the work of your peers and developing your professional judgement. If you successfully achieve these learning outcomes your group experience should be productive. Teams that contain students who do not adequately participate in group activities and/or develop their teamwork skills typically have friction between group members.
Objections:
SPA and SAPA factors will be moderated by the Course Coordinator. Any students believing their peerﾠ assessments were unfair may lodge an objection. Any objection to yourself and peer assessment ratings must be made in writing to the lecturer in charge of the project. Each objection must be a maximum of 500 words (12 point Times New Roman font) clearly outlining why you believe your rating is unfair. Your objection will be discussed with the other members of your group. Objections must be lodged within 3 days from the date that the peer assessment results are released.
An objection usually indicates that at least one member of a group has not achieved the teamwork learning objectives. Marks are only awarded for successfully achieving learning outcomes. The lodgement of an objection will be considered as a request for reassessment of the entire group. Hence if a student lodges an objection the marks for the entire group will be reassessed and released after the objection has been considered. In considering any objection the log books and or meeting minutes for a group will be reviewed.
The course coordinator reserves the final say in application of the SPA factor.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Additional learning resources information
Selected readings as well as other supporting material (e.g. course outline and lecture notes) will be made available during semester via Blackboard.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 1 (28 Jul - 03 Aug) |
Lecture |
General Lecture I Introduction to course including course outline, course content, weekly schedules, learning outcomes, assessment, expectations, guidelines and teaching and learning strategy. Systems engineering concepts. Learning outcomes: L05 |
Lecture |
General Lecture II Mine services and infrastructure. Surface vs underground mining method selection. Learning outcomes: L05 |
|
Week 2 (04 Aug - 10 Aug) |
Lecture |
Surface Mining I Open pit mining: Introduction and principles. Open pit mining: Loading and hauling equipment. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 3 (11 Aug - 17 Aug) |
Lecture |
Surface Mining II Strip mining: Introduction and principles. Strip mining: Draglines, bucket wheel excavators, and dozers. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 4 (18 Aug - 24 Aug) |
Lecture |
Surface Mining III Haul roads and waste dumps. Highwall mining. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 5 (25 Aug - 31 Aug) |
Lecture |
Surface Mining IV Surface miners. Solution mining and other mining methods. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 6 (01 Sep - 07 Sep) |
Lecture |
Underground Mining I Underground mine access and development. Underground mine method selection. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 7 (08 Sep - 14 Sep) |
Lecture |
Underground Mining II Underground coal: Introduction and longwall mining. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 8 (15 Sep - 21 Sep) |
Lecture |
Underground Mining III Underground coal: Thick seam coal mining. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 9 (22 Sep - 28 Sep) |
Lecture |
Underground Mining IV Bord (coal) and room (metal) and pillar mining. Underground metal: Cut and fill stoping. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 10 (06 Oct - 12 Oct) |
Lecture |
Underground Mining V Underground metal: Sublevel stoping. Underground metal: Narrow vein mining. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 11 (13 Oct - 19 Oct) |
Lecture |
Underground Mining VI Underground metal: Caving methods. Learning outcomes: L01, L02, L03, L04, L05 |
Team Based Learning |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L07 |
|
Week 12 (20 Oct - 26 Oct) |
Lecture |
Introduction to Automation in Mining Automation in Mining Learning outcomes: L01, L02, L03, L04, L05, L06 |
Workshop |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L06, L07 |
|
Week 13 (27 Oct - 02 Nov) |
Lecture |
Applications of Automation in Mining Applications of Automation in Mining Learning outcomes: L01, L02, L03, L04, L05, L06 |
Workshop |
Applied Class Learning outcomes: L01, L02, L03, L04, L05, L06, L07 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.